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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Processing Meteorological Data for the CAP-88 PC Model at Los Alamos National Laboratory

The Environmental Protection and Compliance-Compliance Programs (EPC-CP) group at Los Alamos National Laboratory (LANL) uses the Clean Air Act Assessment Package 1988 (CAP-88, Littleton 2020) PC model (Version 4.1) to estimate radiological doses for a set of areal sectors surrounding a release location, in order to satisfy the Environmental Protection Agency (EPA) National Emission Standards for Hazardous Air Pollutants (NESHAP) dose calculation requirement in 40 CFR 61 Subpart H. Among several types of data that must be prepared for CAP-88 input is a text file of meteorological data (“WIND” file), consisting of the joint frequency of wind direction, wind speed, and atmospheric stability categories. EPC-CP produces customized WIND files by running a CAP-88 utility program on a user generated text file of wind data in a different format, known as a STability ARray (STAR) file (Turner, 1964). At LANL, EPC-CP meteorologists prepare customized STAR files with data over desired time periods at selected meteorological towers. A custom program written in Precision Visuals -Workstation Analysis and Visualization Environment (PV-WAVE), a commercial Fortran-like language, is used to read LANL meteorological data and write a STAR file; the executable filename is “Star.out”. However, the outdated PV-WAVE utility program is being phased out by EPC-CP, due to the inefficient process to run it and an inability to modify the code. To preserve the ability to create customized meteorological data for CAP-88 in a way that will be easy to use and maintain, a new replacement utility program, written in the Python programming language, has been developed. The new, improved program reads a data file from any LANL meteorological tower, and at each desired observation time, determines the wind direction, wind speed, and stability categories defined in the CAP-88 documentation. The frequencies of all combinations of the three sets of categories are calculated and written to a file in the STAR format, which can later be converted to a WIND file for input into CAP-88.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2001

Legato: Personal Computer Software for Analyzing Pressure-Sensitive Paint Data

'Legato' is personal computer software for analyzing radiometric pressure-sensitive paint (PSP) data. The software is written in the C programming language and executes under Windows 95/98/NT operating systems. It includes all operations normally required to convert pressure-paint image intensities to normalized pressure distributions mapped to physical coordinates of the test article. The program can analyze data from both single- and bi-luminophore paints and provides for both in situ and a priori paint calibration. In addition, there are functions for determining paint calibration coefficients from calibration-chamber data. The software is designed as a self-contained, interactive research tool that requires as input only the bare minimum of information needed to accomplish each function, e.g., images, model geometry, and paint calibration coefficients (for a priori calibration) or pressure-tap data (for in situ calibration). The program includes functions that can be used to generate needed model geometry files for simple model geometries (e.g., airfoils, trapezoidal wings, rotor blades) based on the model planform and airfoil section. All data files except images are in ASCII format and thus are easily created, read, and edited. The program does not use database files. This simplifies setup but makes the program inappropriate for analyzing massive amounts of data from production wind tunnels. Program output consists of Cartesian plots, false-colored real and virtual images, pressure distributions mapped to the surface of the model, assorted ASCII data files, and a text file of tabulated results. Graphical output is displayed on the computer screen and can be saved as publication-quality (PostScript) files.

Schairer, Edward T.↗
DOE OSTI2018

PeptideListToXML

The PeptideListToXML application reads a tab-delimited text file created by the Peptide Hit Results Processor (PHRP) and creates a PepXML with the appropriate information. The various _SeqInfo files created by PHRP must be present in the same folder as the text file. If the MASIC Scan Stats file is also present, then elution time information will be extracted and included in the PepXML file. You should ideally also include the name of the parameter file used for the MS/MS search engine.

Monroe, Matthew↗
DOE OSTI2020

Kinetic Simulations of Microstructural Evolution (KSOME)

"Kinetic simulations of microstructural evolution" (KSOME) is an object Kinetic Monte Carlo (OMKC) simulation code. It is developed to simulate microstructural evolution in materials during irradiation. KSOME is developed from ground up with priority given to the flexibility, ease of upgradability, and computation efficiency, in that order. With previously developed simulation codes, various processes (more precisely, the diffusion-reaction processes) that can occur in a system were hardwired into the code. Hence, to perform higher fidelity simulations, a significant coding effort was required every time to incorporate either a more accurate description of existing processes or new processes. With KSOME, the necessity for frequent code upgrades whenever there is a need to perform higher fidelity simulations is either eliminated or reduced significantly. In KSOME, the categories of various diffusion-reaction processes and the data-management system are hardwired, while the execution of the diffusion-reaction processes specific to a system is specified via input files. In the present version of KSOME, the analytical expression required to calculate defect interaction radii are inputted via a text file. However, the ability to parse mathematical expressions from a text file can be extended to input the analytical expression to calculate other defect properties; including the expressions to calculate the change in the migration barriers of mobile defects due to long-range interaction with extended defects

Nandipati, Giridhar [Pacific Northwest National La↗
NASA NTRS2008

GIDEP Batching Tool

This software provides internal, automated search mechanics of GIDEP (Government- Industry Data Exchange Program) Alert data imported from the GIDEP government Web site. The batching tool allows the import of a single parts list in tab-delimited text format into the local JPL GIDEP database. Delimiters from every part number are removed. The original part numbers with delimiters are compared, as well as the newly generated list without the delimiters. The two lists run against the GIDEP imports, and output any matches. This feature only works with Netscape 2.0 or greater, or Internet Explorer 4.0 or greater. The user selects the browser button to choose a text file to import. When the submit button is pressed, this script will import alerts from the text file into the local JPL GIDEP database. This batch tool provides complete in-house control over exported material and data for automated batch match abilities. The batching tool has the ability to match capabilities of the parts list to tables, and yields results that aid further research and analysis. This provides more control over GIDEP information for metrics and reports information not provided by the government site. This software yields results quickly and gives more control over external data from the government site in order to generate other reports not available from the external source. There is enough space to store years of data. The program relates to risk identification and management with regard to projects and GIDEP alert information encompassing flight parts for space exploration.

Fong, Danny↗
NASA NTRS1992

PHOTCAL: The IRAF photometric calibration package

The IRAF photmetric calibration package PHOTCAL is discussed. PHOTCAL is a set of tasks designed to derive the transformation from the instrumental photometric system to the standard photometric system, and apply the transformation to the observations. The PHOTCAL package contains tasks for: (1) creating and/or editing standard star catalogs and observations catalogs, (2) creating, checking and editing the configuration file which specifies the format of the standard star and observations catalogs and the form of the transformation equations, (3) solving the transformation equations interactively or non-iteractively using non-linear least squares fitting routines, and (4) applying the transformation to the observations. PHOTCAL standard star and observations catalogs are simple text files, whose columns are delimited by whitespace, and whose first column contains the star names. This format makes it relatively easy to interface the output of non-IRAF photometry programs as well as the output of the IRAF APPHOT and DAOPHOT photometry packages to PHOTCAL. PHOTCAL maintains a standard star catalog directory for the convenience of the user, but users can easily create their own standard star catalogs and/or define their own standard star catalog directory. Separate observations files produced by APPHOT, DAOPHOT or a user program containing data for stellar fields taken through different filters, can be combined into observations catalogs using one of the PHOTCAL preprocessor tasks. The input configuration file required by PHOTCAL is a text file, consisting of a series of instructions written by the user in a mini-language understood by the PHOTCAL parser. These instructions: (1) assign names to the input data columns in the standard star and observations catalogs, (2) assign names and initial values to the parameters to be fit, (3) define and describe how to solve the transformation equations. The mini-language approach permits great flexibility in the format of the input catalogs and the form of the transformation equations.

Davis, L. E.↗
NASA NTRS2020

AJAX CABOTS Data

The Alpha Jet Atmospheric eXperiment (AJAX) airborne science project based out of NASA Ames Research Center performed eight science flights in coordination with the California Baseline Ozone Transport Study (CABOTS) campaign. Many of these flights included a series of vertical profiles (~ 0-5 km) distributed roughly along either a North/South or East/West transect. Some flights also connected the fixed-location measurements at Visalia (TOPAZ ozone lidar) and Bodega Bay (ozonesondes). AJAX measured ozone, carbon dioxide, methane, water vapor, and 3-D winds on each flight, and those in situ measurements are the basis of the data sets collected here. Trace gas data sets including time and aircraft position have been delivered as comma-separated-value text files. Meteorological data (temperature, pressure and 3-dimensional winds) are provided at 1 Hz in ICARTT-compliant text files.

Iraci, Laura T.↗
DOE OSTI2024

Data Format and Descriptions for the Alabama Carbon Storage: Data Sharing and Engagement Project

The Alabama Carbon Storage: Data Sharing and Engagement (ACS-DSE) project seeks to develop publicly accessible geologic carbon storage models and data across the southern Gulf Coastal Plain of Alabama. The public online platform developed for this project will include geologic, geophysical, infrastructure, and other relevant datasets and geologic models of the study area. Datasets, model surfaces (e.g. structural contour maps, isolith maps, porosity maps), and infrastructure data (e.g. offshore pipelines, field boundaries) will be downloadable in commonly used file formats. The anticipated primary geologic datasets are well headers, formation tops, average reservoir properties, and core analyses; these will be available as commaseparated values (CSV) text files and MS Excel workbooks. Geophysical logs will be available in Log ASCII Standard (LAS) file format. Modeled surfaces, such as structure contour maps, will be available in ArcGIS formats and text files. Infrastructure data will be available as ArcGIS shapefiles. This document provides information on the data sources and attributes of the datasets.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2021

Archparse

Archparse is a Python package that holds the purpose and capability of converting the contents of a text file to a functioning neural network based on the Tensorflow 2.X framework. This is able to be done with minimal written Python code and next to no knowledge of how to build models with Tensorflow directly. More specifically Archparse parses a text file with extension ".arch" which contains neural network architecture information that corresponds to either the Tensorflow 2.X API or custom code written with the Tensorflow 2.X API. Included in the initial version is the capacity to easily produce sequential autoencoders and sequential neural networks.

Vander Wal, MichaelD.↗
DOE OSTI2016

rsed

"rsed" is an R package that contains tools for stream editing: manipulating text files by making insertions, replacements, deletions, substitutions, or commenting. It hails from the powerful Unix command, "sed". While the "rsed" package is not nearly as powerful as "see", it is much simpler to use. R programmers often write scripts that may require simple manipulation of text files. "rsed" addresses that need.

Source record↗
DOE OSTI2016

rsed

"rsed" is an R package that contains tools for stream editing: manipulating text files by making insertions, replacements, deletions, substitutions, or commenting. It hails from the powerful Unix command, "sed". While the "rsed" package is not nearly as powerful as "see", it is much simpler to use. R programmers often write scripts that may require simple manipulation of text files. "rsed" addresses that need.

Source record↗
DOE OSTI2020

EGS Collab Experiment 1: 3D Seismic Velocity Model and Updated Microseismic Catalog Using Transfer-Learning Aided Double-Difference Tomography

This package contains a 3D Seismic velocity model and an updated microseismic catalog associated with a proceedings paper (Chai et al., 2020) published in the 45th Workshop on Geothermal Reservoir Engineering. The 3D_seismic_velocity_model text file contains x (m), y(m), z(m), P-wave velocity (km/s), P-wave velocity quality indicator (1 for well-constrained; 0 for poorly constrained), S-wave velocity (km/s), and S-wave velocity quality indicator (1 for well-constrained; 0 for poorly constrained). The Updated_MEQ_catalog text file contains event origin time, x(m), y(m), z(m), error in x (m), error in y (m), error in z (m), and RMS misfit (millisecond). The 3D_seismic_P-wave_velocity_model animation file shows slices of the 3D P-wave velocity model. The 3D_seismic_S-wave_velocity_model animation file shows slices of the 3D S-wave velocity model. The Interactive_MEQ_locations API file is an interactive visualization of the updated microseismic event locations. The visualization allows users to view the event locations by dragging, rotating, and zooming in. References: Chai, C., Maceira, M., Santos-Villalobos, H. J., Venkatakrishnan, S. V., Schoenball, M., and EGS Collab Team, 2020, Automatic Seismic Phase Picking Using Deep Learning for the EGS Collab Project, in PROCEEDINGS, 45th Workshop on Geothermal Reservoir Engineering, edited, Stanford University, Stanford, California, 45, 1266-1276.

15 GEOTHERMAL ENERGY↗
DOE OSTI2020

EGS Collab Experiment 1: 3D Seismic Velocity Model and Updated Microseismic Catalog from Double-Difference Seismic Tomography

This package contains a 3D Seismic velocity model and an updated microseismic catalog obtained for a double-difference seismic tomography study. The 3D_seismic_velocity_model text file contains x (m), y(m), z(m), P-wave velocity (km/s), P-wave velocity quality indicator (1 for well-constrained; 0 for poorly constrained), S-wave velocity (km/s), and S-wave velocity quality indicator (1 for well-constrained; 0 for poorly constrained). The Updated_MEQ_catalog text file contains event origin time, x(m), y(m), z(m), error in x (m), error in y (m), error in z (m), and RMS misfit (millisecond). The 3D_seismic_P-wave_velocity_model animation file shows slices of the 3D P-wave velocity model. The 3D_seismic_S-wave_velocity_model animation file shows slices of the 3D S-wave velocity model. The Interactive_MEQ_location_comparison API file is an interactive visualization of the updated microseismic event locations and the original seismic catalog. The visualization allows users to view and compare the event locations by dragging, rotating, and zooming in. An updated version of 3D_seismic_velocity_model and associated animations were included, which were calculated with a more strict assumption for quality indicators.

15 GEOTHERMAL ENERGY↗
DOE OSTI2017

Workbench Analysis Sequence Processor

The Workbench Analysis Sequence Processor (WASP) was developed to streamline lexing, parsing, access, validation, and analysis of ascii text files. The foundation of WASP resides on the parse tree data structure, where each node in the tree represents the syntax of the input document. Nodes can parent nodes with children. Nodes that have no children are known as terminal or leaf nodes , and they represent tokens (string, number, delimiter, etc.) in the text file. The fast lexical analyzer generator (flex - https://www.gnu.org/software/flex/) and GNU Bison parser generator (https://www.gnu.org/software/bison/) are extensively used for lexing and parsing.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2019

Utah FORGE: Earth Model Native State Simulation Results

Utah FORGE phase 2C Native State Simulation zip contains the data used for the boundary conditions and subsequent native state simulation results obtained using the simulation code FALCON. Data are from the nodes of the simulation domain, with used a uniform 50m spacing over a 2500 X 2500 X 2750m domain approximately centered on the FORGE footprint. There is also a read me text file, that is included, containing metadata. The Reservoir Porosity and Upscale DFN Permeability zip contains the data used for the spatial distribution of the anisotropic permeability and porosity used in the native state simulation of the Utah FORGE site. Please contact Robert Podgorney at the Idaho National Laboratory with questions, robert.podgorney@inl.gov. There is also a read me text file included containing metadata.

15 GEOTHERMAL ENERGY↗
NASA NTRS2003

XML-Based Generator of C++ Code for Integration With GUIs

An open source computer program has been developed to satisfy a need for simplified organization of structured input data for scientific simulation programs. Typically, such input data are parsed in from a flat American Standard Code for Information Interchange (ASCII) text file into computational data structures. Also typically, when a graphical user interface (GUI) is used, there is a need to completely duplicate the input information while providing it to a user in a more structured form. Heretofore, the duplication of the input information has entailed duplication of software efforts and increases in susceptibility to software errors because of the concomitant need to maintain two independent input-handling mechanisms. The present program implements a method in which the input data for a simulation program are completely specified in an Extensible Markup Language (XML)-based text file. The key benefit for XML is storing input data in a structured manner. More importantly, XML allows not just storing of data but also describing what each of the data items are. That XML file contains information useful for rendering the data by other applications. It also then generates data structures in the C++ language that are to be used in the simulation program. In this method, all input data are specified in one place only, and it is easy to integrate the data structures into both the simulation program and the GUI. XML-to-C is useful in two ways: 1. As an executable, it generates the corresponding C++ classes and 2. As a library, it automatically fills the objects with the input data values.

Hua, Hook↗
NASA NTRS2007

Driver Code for Adaptive Optics

A special-purpose computer code for a deformable-mirror adaptive-optics control system transmits pixel-registered control from (1) a personal computer running software that generates the control data to (2) a circuit board with 128 digital-to-analog converters (DACs) that generate voltages to drive the deformable-mirror actuators. This program reads control-voltage codes from a text file, then sends them, via the computer s parallel port, to a circuit board with four AD5535 (or equivalent) chips. Whereas a similar prior computer program was capable of transmitting data to only one chip at a time, this program can send data to four chips simultaneously. This program is in the form of C-language code that can be compiled and linked into an adaptive-optics software system. The program as supplied includes source code for integration into the adaptive-optics software, documentation, and a component that provides a demonstration of loading DAC codes from a text file. On a standard Windows desktop computer, the software can update 128 channels in 10 ms. On Real-Time Linux with a digital I/O card, the software can update 1024 channels (8 boards in parallel) every 8 ms.

Rao, Shanti↗